TPL2 kinase expression is regulated by the p38γ/p38δ-dependent association of aconitase-1 with TPL2 mRNA.

p38γ and p38δ (p38γ/p38δ) regulate inflammation, in part by controlling tumor progression locus 2 (TPL2) expression in myeloid cells. Here, we demonstrate that TPL2 protein levels are dramatically reduced in p38γ/p38δ-deficient (p38γ/δ-/-) cells and tissues without affecting TPL2 messenger ribonucleic acid (mRNA) expression. We show that p38γ/p38δ posttranscriptionally regulates the TPL2 amount at two different levels. p38γ/p38δ interacts with the TPL2/A20 Binding Inhibitor of NF-κB2 (ABIN2)/Nuclear Factor κB1p105 (NF-κB1p105) complex, increasing TPL2 protein stability. Additionally, p38γ/p38δ regulates TPL2 mRNA translation by modulating the repressor function of TPL2 3' Untranslated region (UTR) mediated by its association with aconitase-1 (ACO1). ACO1 overexpression in wild-type cells increases the translational repression induced by TPL2 3'UTR and severely decreases TPL2 protein levels. p38δ binds to ACO1, and p38δ expression in p38γ/δ-/- cells fully restores TPL2 protein to wild-type levels by reducing the translational repression of TPL2 mRNA. This study reveals a unique mechanism of posttranscriptional regulation of TPL2 expression, which given its central role in innate immune response, likely has great relevance in physiopathology.

PPARγ attenuates cellular senescence of alveolar macrophages in asthma-COPD overlap.

BACKGROUND: Asthma-chronic obstructive pulmonary disease (COPD) overlap (ACO) represents a complex condition characterized by shared clinical and pathophysiological features of asthma and COPD in older individuals. However, the pathophysiology of ACO remains unexplored. We aimed to identify the major inflammatory cells in ACO, examine senescence within these cells, and elucidate the genes responsible for regulating senescence. METHODS: Bioinformatic analyses were performed to investigate major cell types and cellular senescence signatures in a public single-cell RNA sequencing (scRNA-Seq) dataset derived from the lung tissues of patients with ACO. Similar analyses were carried out in an independent cohort study Immune Mechanisms Severe Asthma (IMSA), which included bulk RNA-Seq and CyTOF data from bronchoalveolar lavage fluid (BALF) samples. RESULTS: The analysis of the scRNA-Seq data revealed that monocytes/ macrophages were the predominant cell type in the lung tissues of ACO patients, constituting more than 50% of the cells analyzed. Lung monocytes/macrophages from patients with ACO exhibited a lower prevalence of senescence as defined by lower enrichment scores of SenMayo and expression levels of cellular senescence markers. Intriguingly, analysis of the IMSA dataset showed similar results in patients with severe asthma. They also exhibited a lower prevalence of senescence, particularly in airway CD206 + macrophages, along with increased cytokine expression (e.g., IL-4, IL-13, and IL-22). Further exploration identified alveolar macrophages as a major subtype of monocytes/macrophages driving cellular senescence in ACO. Differentially expressed genes related to oxidation-reduction, cytokines, and growth factors were implicated in regulating senescence in alveolar macrophages. PPARγ (Peroxisome Proliferator-Activated Receptor Gamma) emerged as one of the predominant regulators modulating the senescent signature of alveolar macrophages in ACO. CONCLUSION: The findings suggest that senescence in macrophages, particularly alveolar macrophages, plays a crucial role in the pathophysiology of ACO. Furthermore, PPARγ may represent a potential therapeutic target for interventions aimed at modulating senescence-associated processes in ACO.Key words ACO, Asthma, COPD, Macrophages, Senescence, PPARγ.

Early-life house dust mite aeroallergen exposure augments cigarette smoke-induced myeloid inflammation and emphysema in mice.

BACKGROUND: Longitudinal studies have identified childhood asthma as a risk factor for obstructive pulmonary disease (COPD) and asthma-COPD overlap (ACO) where persistent airflow limitation can develop more aggressively. However, a causal link between childhood asthma and COPD/ACO remains to be established. Our study aimed to model the natural history of childhood asthma and COPD and to investigate the cellular/molecular mechanisms that drive disease progression. METHODS: Allergic airways disease was established in three-week-old young C57BL/6 mice using house dust mite (HDM) extract. Mice were subsequently exposed to cigarette smoke (CS) and HDM for 8 weeks. Airspace enlargement (emphysema) was measured by the mean linear intercept method. Flow cytometry was utilised to phenotype lung immune cells. Bulk RNA-sequencing was performed on lung tissue. Volatile organic compounds (VOCs) in bronchoalveolar lavage-fluid were analysed to screen for disease-specific biomarkers. RESULTS: Chronic CS exposure induced emphysema that was significantly augmented by HDM challenge. Increased emphysematous changes were associated with more abundant immune cell lung infiltration consisting of neutrophils, interstitial macrophages, eosinophils and lymphocytes. Transcriptomic analyses identified a gene signature where disease-specific changes induced by HDM or CS alone were conserved in the HDM-CS group, and further revealed an enrichment of Mmp12, Il33 and Il13, and gene expression consistent with greater expansion of alternatively activated macrophages. VOC analysis also identified four compounds increased by CS exposure that were paradoxically reduced in the HDM-CS group. CONCLUSIONS: Early-life allergic airways disease worsened emphysematous lung pathology in CS-exposed mice and markedly alters the lung transcriptome.

Neopterin in patients with COPD, asthma, and ACO: association with endothelial and lung functions.

BACKGROUND AND OBJECTIVE: Endothelial dysfunction has been widely recognized in chronic airway diseases, including chronic obstructive pulmonary disease (COPD) and asthma; however, it remains unclear in asthma-COPD overlap (ACO). Neopterin (NP), a metabolite of guanosine triphosphate, is a novel biomarker for identifying the increased risk of adverse cardiovascular events. This study aims to investigate the association of NP with endothelial dysfunction and impaired lung function in COPD, asthma, and ACO patients. METHODS: A total of 77 subjects were prospectively recruited. All the participants underwent lung function test, endothelial function evaluation, including pulse wave velocity (PWV) and flow-mediated dilation (FMD), and blood sample detection. Moreover, the effect of NP on endothelial cells (ECs) in anoxic environments was assessed in vitro. RESULTS: Endothelial function was significantly decreased in the COPD and ACO patients compared with that in the healthy controls (P < 0.05). Forced expiratory volume in 1 s (FEV1) was negatively correlated with PWV and positively correlated with FMD (P < 0.05). NP was significantly increased in patients with chronic respiratory diseases compared with that in the control group, with COPD being the highest, followed by asthma, and ACO as the last (P < 0.05). The plasma level of NP exhibited negative correlations with FEV1 and positive correlations with PWV (P < 0.05). In vitro, a high level of NP increased the reactive oxygen species (ROS) and decreased the mitochondrial membrane potential (ΔΨm) of ECs dose-dependently in a hypoxic environment (P < 0.05). CONCLUSION: NP was related to disease severity of chronic airway diseases and involved in the pathogenesis of endothelial dysfunction. A high NP level may contribute to endothelial dysfunction by increasing the oxidative stress of ECs dose-dependently in a hypoxic environment. Our findings may provide a novel evaluation and therapeutic target for endothelial dysfunction related to chronic airway diseases.

Medicare Payments and ACOs for Dementia Patients Across Race and Social Vulnerability.

OBJECTIVES: This study investigated variations in Medicare payments for Alzheimer's disease and related dementia (ADRD) by race, ethnicity, and neighborhood social vulnerability, together with cost variations by beneficiaries' enrollment in Accountable Care Organizations (ACOs). METHODS: We used merged datasets of longitudinal Medicare Beneficiary Summary File (2016-2020), the Social Vulnerability Index (SVI), and the Medicare Shared Savings Program (MSSP) ACO to measure beneficiary-level ACO enrollment at the diagnosis year of ADRD. We analyzed Medicare payments for patients newly diagnosed with ADRD for the year preceding the diagnosis and for the subsequent 3 years. The dataset included 742,175 Medicare fee-for-service (FFS) beneficiaries aged 65 and older with a new diagnosis of ADRD in 2017 who remained in the Medicare FFS plan from 2016 to 2020. RESULTS: Among those newly diagnosed, Black and Hispanic patients encountered higher total costs compared to White patients, and ADRD patients living in the most vulnerable areas experienced the highest total costs compared to patients living in other regions. These cost differences persisted over 3 years postdiagnosis. Patients enrolled in ACOs incurred lower costs across all racial and ethnic groups and SVI areas. For ADRD patients living in the areas with the highest vulnerability, the cost differences by ACO enrollment of the total Medicare costs ranged from $4,403.1 to $6,922.7, and beneficiaries' savings ranged from $114.5 to $726.6 over three years post-ADRD diagnosis by patient's race and ethnicity. CONCLUSIONS: Black and Hispanic ADRD patients and ADRD patients living in areas with higher social vulnerability would gain more from ACO enrollment compared to their counterparts.

Multiple-Junction-Based Traffic-Aware Routing Protocol Using ACO Algorithm in Urban Vehicular Networks.

The burgeoning interest in intelligent transportation systems (ITS) and the widespread adoption of in-vehicle amenities like infotainment have spurred a heightened fascination with vehicular ad-hoc networks (VANETs). Multi-hop routing protocols are pivotal in actualizing these in-vehicle services, such as infotainment, wirelessly. This study presents a novel protocol called multiple junction-based traffic-aware routing (MJTAR) for VANET vehicles operating in urban environments. MJTAR represents an advancement over the improved greedy traffic-aware routing (GyTAR) protocol. MJTAR introduces a distributed mechanism capable of recognizing vehicle traffic and computing curve metric distances based on two-hop junctions. Additionally, it employs a technique to dynamically select the most optimal multiple junctions between source and destination using the ant colony optimization (ACO) algorithm. We implemented the proposed protocol using the network simulator 3 (NS-3) and simulation of urban mobility (SUMO) simulators and conducted performance evaluations by comparing it with GSR and GyTAR. Our evaluation demonstrates that the proposed protocol surpasses GSR and GyTAR by over 20% in terms of packet delivery ratio, with the end-to-end delay reduced to less than 1.3 s on average.

Optimizing Driving Parameters of the Jumbo Drill Efficiently with XGBoost-DRWIACO Framework: Applied to Increase the Feed Speed.

The jumbo drill is a commonly used driving equipment in tunnel engineering. One of the key decision-making issues for reducing tunnel construction costs is to optimize the main driving parameters to increase the feed speed of the jumbo drill. The optimization of the driving parameters is supposed to meet the requirements of high reliability and efficiency due to the high risk and complex working conditions in tunnel engineering. The flaws of the existing optimization algorithms for driving parameter optimization lie in the low accuracy of the evaluation functions under complex working conditions and the low efficiency of the algorithms. To address the above problems, a driving parameter optimization method based on the XGBoost-DRWIACO framework with high accuracy and efficiency is proposed. A data-driven prediction model for feed speed based on XGBoost is established as the evaluation function, which has high accuracy under complex working conditions and ensures the high reliability of the optimized results. Meanwhile, an improved ant colony algorithm based on dimension reduction while iterating strategy (DRWIACO) is proposed. DRWIACO is supposed to improve efficiency by resolving inefficient iterations of the ant colony algorithm (ACO), which is manifested as falling into local optimum, converging slowly and converging with a slight fluctuation in a certain dimension. Experimental results show that the error by the proposed framework is less than 10%, and the efficiency is increased by over 30% compared with the comparison methods, which meets the requirements of high reliability and efficiency for tunnel construction. More importantly, the construction cost is reduced by 19% compared with the actual feed speed, which improves the economic benefits.

Characterization and Potential Action Mode Divergences of Homologous ACO1 Genes during the Organ Development and Ripening Process between Non-Climacteric Grape and Climacteric Peach.

Ethylene is one crucial phytohormone modulating plants' organ development and ripening process, especially in fruits, but its action modes and discrepancies in non-climacteric grape and climacteric peach in these processes remain elusive. This work is focused on the action mode divergences of ethylene during the modulation of the organ development and ripening process in climacteric/non-climacteric plants. We characterized the key enzyme genes in the ethylene synthesis pathway, VvACO1 and PpACO1, and uncovered that their sequence structures are highly conserved, although their promoters exhibit important divergences in the numbers and types of the cis-elements responsive to hormones, implying various responses to hormone signals. Subsequently, we found the two have similar expression modes in vegetative organ development but inverse patterns in reproductive ones, especially in fruits. Then, VvACO1 and PpACO1 were further validated in promoting fruit ripening functions through their transient over-expression/RNAi-expression in tomatoes, of which the former possesses a weaker role than the latter in the fruit ripening process. Our findings illuminated the divergence in the action patterns and function traits of the key VvACO1/PpACO1 genes in the tissue development of climacteric/non-climacteric plants, and they have implications for further gaining insight into the interaction mechanism of ethylene signaling during the modulation of the organ development and ripening process in climacteric/non-climacteric plants.

Ethylene induced AcNAC3 and AcNAC4 take part in ethylene synthesis through mediating AcACO1 during kiwifruit (Actinidia chinensis) ripening.

BACKGROUND: Ethylene plays a vital role in the ripening process of kiwifruit. A terrific amount of transcription factors (TFs) have been shown to regulate ethylene synthesis in various fruits. RESULTS: In this research, two new NAC TFs, named AcNAC3 and AcNAC4, were isolated from kiwifruit, which belonged to NAM subfamily. Bioinformatics analysis showed that both AcNAC3 and AcNAC4 were hydrophilic proteins with similar three-dimensional structures. The expression levels of AcNAC3, AcNAC4 and AcACO1 increased during kiwifruit ripening, as well as were induced by ethylene and repressed by 1-methylcyclopropene (1-MCP). Correlation analysis exhibited that ethylene production was positively correlated with the expression levels of AcNAC3, AcNAC4 and AcACO1. Moreover, both AcNAC3 and AcNAC4 acted as transcriptional activators and could bind to and activate AcACO1 promoter. CONCLUSION: All results unveiled that the ethylene-induced AcNAC3 and AcNAC4 were transcriptional activators, and might participate in kiwifruit ripening and ethylene biosynthesis through activating AcACO1, providing a new insight of ethylene synthetic regulation during kiwifruit ripening. © 2024 Society of Chemical Industry.

Anti-Inflammatory Effects of Serotonin Receptor and Transient Receptor Potential Channel Ligands in Human Small Intestinal Epithelial Cells.

Intestinal inflammation and dysbiosis can lead to inflammatory bowel diseases (IBD) and systemic inflammation, affecting multiple organs. Developing novel anti-inflammatory therapeutics is crucial for preventing IBD progression. Serotonin receptor type 2A (5-HT2A) ligands, including psilocybin (Psi), 4-Acetoxy-N,N-dimethyltryptamine (4-AcO-DMT), and ketanserin (Ket), along with transient receptor potential (TRP) channel ligands like capsaicin (Cap), curcumin (Cur), and eugenol (Eug), show promise as anti-inflammatory agents. In this study, we investigated the cytotoxic and anti-inflammatory effects of Psi, 4-AcO-DMT, Ket, Cap, Cur, and Eug on human small intestinal epithelial cells (HSEIC). HSEIC were exposed to tumor necrosis factor (TNF)-α and interferon (IFN)-γ for 24 h to induce an inflammatory response, followed by treatment with each compound at varying doses (0-800 µM) for 24 to 96 h. The cytotoxicity was assessed using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay and protein expression by Western blot (WB) analysis. As single treatments, Psi (40 µM), Cur (0.5 µM), and Eug (50 µM) significantly reduced COX-2 levels without cytotoxic effects. When combined, Psi (40 µM) and Cur (0.5 µM) exhibited synergy, resulting in a substantial decrease in COX-2 protein levels (-28× fold change), although the reduction in IL-6 was less pronounced (-1.6× fold change). Psi (20 µM) and Eug (25 µM) demonstrated the most favorable outcomes, with significant decreases in COX-2 (-19× fold change) and IL-6 (-10× fold change) protein levels. Moreover, the combination of Psi and Eug did not induce cytotoxic effects in vitro at any tested doses. This study is the first to explore the anti-inflammatory potential of psilocybin and 4-AcO-DMT in the intestines while highlighting the potential for synergy between the 5-HT2A and TRP channel ligands, specifically Psi and Eug, in alleviating the TNF-α/IFN-γ-induced inflammatory response in HSEIC. Further investigations should evaluate if the Psi and Eug combination has the therapeutic potential to treat IBD in vivo.

GhXB38D represses cotton fibre elongation through ubiquitination of ethylene biosynthesis enzymes GhACS4 and GhACO1.

Ethylene plays an essential role in the development of cotton fibres. Ethylene biosynthesis in plants is elaborately regulated by the activities of key enzymes, 1-aminocyclopropane-1-carboxylate oxidase (ACO) and 1-aminocyclopropane-1-carboxylate synthase (ACS); however, the potential mechanism of post-translational modification of ACO and ACS to control ethylene synthesis in cotton fibres remains unclear. Here, we identify an E3 ubiquitin ligase, GhXB38D, that regulates ethylene biosynthesis during fibre elongation in cotton. GhXB38D gene is highly expressed in cotton fibres during the rapid elongation stage. Suppressing GhXB38D expression in cotton significantly enhanced fibre elongation and length, accompanied by the up-regulation of genes associated with ethylene signalling and fibre elongation. We demonstrated that GhXB38D interacts with the ethylene biosynthesis enzymes GhACS4 and GhACO1 in elongating fibres and specifically mediates their ubiquitination and degradation. The inhibition of GhXB38D gene expression increased the stability of GhACS4 and GhACO1 proteins in cotton fibres and ovules, resulting in an elevated concentration of ethylene. Our findings highlight the role of GhXB38D as a regulator of ethylene synthesis by ubiquitinating ACS4 and ACO1 proteins and modulating their stability. GhXB38D acts as a negative regulator of fibre elongation and serves as a potential target for enhancing cotton fibre yield and quality through gene editing strategy.

Airway inflammatory changes in the lungs of patients with asthma-COPD overlap (ACO): a bronchoscopy endobronchial biopsy study.

BACKGROUND: Although asthma and chronic obstructive pulmonary disease (COPD) are two distinct chronic airway inflammatory diseases, they often co-exist in a patient and the condition is referred to as asthma-COPD overlap (ACO). Lack of evidence regarding the inflammatory cells in ACO airways has led to their poor prognosis and treatment. The objective of this endobronchial biopsy (EBB) study was to enumerate inflammatory cellular changes in the airway wall of ACO compared with asthma, COPD current smokers (CS) and ex-smokers (ES), normal lung function smokers (NLFS), and non-smoker controls (HC). METHODS: EBB tissues from 74 patients were immunohistochemically stained for macrophages, mast cells, eosinophils, neutrophils, CD8+ T-cells and CD4+ T-cells. The microscopic images of stained tissues were evaluated in the epithelium, reticular basement membrane (RBM) cells/mm RBM length, and lamina propria (LP) cells/mm2 up to a depth of 120 µM using the image analysis software Image-Pro Plus 7.0. The observer was blinded to the images and disease diagnosis. Statistical analysis was performed using GraphPad Prism v9. RESULTS: The tissue macrophages in ACO were substantially higher in the epithelium and RBM than in HC (P < 0.001 for both), COPD-ES (P < 0.001 for both), and -CS (P < 0.05 and < 0.0001, respectively). The ACO LP macrophages were significantly higher in number than COPD-CS (P < 0.05). The mast cell numbers in ACO were lower than in NLFS (P < 0.05) in the epithelium, lower than COPD (P < 0.05) and NLFS (P < 0.001) in RBM; and lower than  HC (P < 0.05) in LP. We noted lower eosinophils in ACO LP than HC (P < 0.05) and the lowest neutrophils in both ACO and asthma. Furthermore, CD8+ T-cell numbers increased in the ACO RBM than HC (P < 0.05), COPD-ES (P < 0.05), and NLFS (P < 0.01); however, they were similar in number in epithelium and LP across groups. CD4+ T-cells remained lower in number across all regions and groups. CONCLUSION: These results suggest that the ACO airway tissue inflammatory cellular profile differed from the contributing diseases of asthma and COPD with a predominance of macrophages.

Picturing asthma in Turkey: results from the Turkish adult asthma registry.

INTRODUCTION: National data on asthma characteristics and the factors associated with uncontrolled asthma seem to be necessary for every country. For this purpose, we developed the Turkish Adult Asthma Registry for patients with asthma aiming to take a snapshot of our patients, thereby assigning the unmet needs and niche areas of intervention. METHODS: Case entries were performed between March 2018 and March 2022. A web-based application was used to record data. Study outcomes were demographic features, disease characteristics, asthma control levels, and phenotypes. RESULTS: The registry included 2053 patients from 36 study centers in Turkey. Female subjects dominated the group (n = 1535, 74.8%). The majority of the patients had allergic (n = 1158, 65.3%) and eosinophilic (n = 1174, 57.2%) asthma. Six hundred nineteen (32.2%) of the patients had obese asthma. Severe asthma existed in 670 (32.6%) patients. Majority of cases were on step 3-5 treatment (n: 1525; 88.1%). Uncontrolled asthma was associated with low educational level, severe asthma attacks in the last year, low FEV1, existence of chronic rhinosinusitis and living in particular regions. CONCLUSION: The picture of this registry showed a dominancy of middle-aged obese women with moderate-to-severe asthma. We also determined particular strategic targets such as low educational level, severe asthma attacks, low FEV1, and chronic rhinosinusitis to decrease uncontrolled asthma in our country. Moreover, some regional strategies may also be needed as uncontrolled asthma is higher in certain regions. We believe that these data will guide authorities to reestablish national asthma programs to improve asthma service delivery.

KPCA-WRF-prediction of heart rate using deep feature fusion and machine learning classification with tuned weighted hyper-parameter.

The rapid advancement of technology such as stream processing technologies, deep-learning approaches, and artificial intelligence plays a prominent and vital role, to detect heart rate using a prediction model. However, the existing methods could not handle high -dimensional datasets, and deep feature learning to improvise the performance. Therefore, this work proposed a real-time heart rate prediction model, using K-nearest neighbour (KNN) adhered to the principle component analysis algorithm (PCA) and weighted random forest algorithm for feature fusion (KPCA-WRF) approach and deep CNN feature learning framework. The feature selection, from the fused features, was optimized by ant colony optimization (ACO) and particle swarm optimization (PSO) algorithm to enhance the selected fused features from deep CNN. The optimized features were reduced to low dimensions using the PCA algorithm. The significant straight heart rate features are plotted by capturing out nearest similar data point values using the algorithm. The fused features were then classified for aiding the training process. The weighted values are assigned to those tuned hyper parameters (feature matrix forms). The optimal path and continuity of the weighted feature representations are moved using the random forest algorithm, in K-fold validation iterations.

A novel treatment strategy to prevent Parkinson's disease: focus on iron regulatory protein 1 (IRP1).

We propose that neural damage in Parkinson's disease (PD) is due to dysregulation of iron utilization rather than to high iron levels per se. Iron deposits are associated with neuronal cell death in substantia nigra (SN) resulting in PD where high levels of iron in SNs are due to dysregulation of iron utilization. Cytosolic aconitase (ACO1) upon losing an iron-sulfur cluster becomes iron regulatory protein 1 (IRP1). Rotenone increases levels of IRP1 and induces PD in rats. An increase in iron leads to inactivation of IRP1. We propose a novel treatment strategy to prevent PD. Specifically in rats given rotenone by subcutaneous injections, iron, from iron carbonyl from which iron is slowly absorbed, given three times a day by gavage will keep iron levels constant in the gut whereby iron levels and iron utilization systematically can be tightly regulated. Rotenone adversely affects complex 1 iron-sulfur proteins. Iron supplementation will increase iron-sulfur cluster formation switching IRP1 to ACO1. With IRP1 levels kept constantly low, iron utilization will systematically be tightly regulated stopping dysregulation of complex 1 and the neural damage done by rotenone preventing PD.

Enhanced QoS Routing Protocol for an Unmanned Ground Vehicle, Based on the ACO Approach.

Improving models for managing the networks of firefighting unmanned ground vehicles in crowded areas, as a recommendation system (RS), represented a difficult challenge. This challenge comes from the peculiarities of these types of networks. These networks are distinguished by the network coverage area size, frequent network connection failures, and quick network structure changes. The research aims to improve the communication network of self-driving firefighting unmanned ground vehicles by determining the best routing track to the desired fire area. The suggested new model intends to improve the RS regarding the optimum tracking route for firefighting unmanned ground vehicles by employing the ant colony optimization technique. This optimization method represents one of the swarm theories utilized in vehicles ad-hoc networks and social networks. According to the results, the proposed model can enhance the navigation of self-driving firefighting unmanned ground vehicles towards the fire region, allowing firefighting unmanned ground vehicles to take the shortest routes possible, while avoiding closed roads and traffic accidents. This study aids in the control and management of ad-hoc vehicle networks, vehicles of everything, and the internet of things.

Heterogeneous Network Switching Strategy Based on Communication Blind Area Dwell Time.

The limitation of indoor visible light coverage and the attenuation of its signal when propagating in line-of-sight has seriously affected the stable communication of receiving devices when users move randomly and also aggravated the power consumption of visible light networking systems. According to the above situation, on the basis of the heterogeneous networking of visible light communication (VLC) and RF communication integration, this article proposes a horizontal-vertical collaborative handover strategy based on the communication blind area dwell time (CBD-HVHO). Combining asymmetrically clipped optical orthogonal frequency division multiplexing (ACO-OFDM) technology with networking handover technology, ACO-OFDM is used to determine the indoor communication blind area by calculating the bit error rate (BER) value at the signal receiver while reducing the multipath interference generated by visible light signals during channel transmission. To achieve this, set the communication blind channel interruption time as the threshold time, compare the communication blind area dwell time with the threshold time, and finally combine the horizontal and vertical collaborative handover strategies based on the communication blind area dwell time. The simulation results show that the handover probability is 0.009, the average number of handovers is 1.006, and the average network throughput is 195.2826 Mbps. Compared with the previously proposed immediate vertical handover (I-VHO) scheme and the dwell vertical handover (D-VHO) scheme, the communication stability is significantly improved, and the power consumption of the network system is reduced to a certain extent.

An Efficient Trust-Aware Task Scheduling Algorithm in Cloud Computing Using Firefly Optimization.

Task scheduling in the cloud computing paradigm poses a challenge for researchers as the workloads that come onto cloud platforms are dynamic and heterogeneous. Therefore, scheduling these heterogeneous tasks to the appropriate virtual resources is a huge challenge. The inappropriate assignment of tasks to virtual resources leads to the degradation of the quality of services and thereby leads to a violation of the SLA metrics, ultimately leading to the degradation of trust in the cloud provider by the cloud user. Therefore, to preserve trust in the cloud provider and to improve the scheduling process in the cloud paradigm, we propose an efficient task scheduling algorithm that considers the priorities of tasks as well as virtual machines, thereby scheduling tasks accurately to appropriate VMs. This scheduling algorithm is modeled using firefly optimization. The workload for this approach is considered by using fabricated datasets with different distributions and the real-time worklogs of HPC2N and NASA were considered. This algorithm was implemented by using a Cloudsim simulation environment and, finally, our proposed approach is compared over the baseline approaches of ACO, PSO, and the GA. The simulation results revealed that our proposed approach has shown a significant impact over the baseline approaches by minimizing the makespan, availability, success rate, and turnaround efficiency.

A Quality-of-Service-Aware Service Composition Method in the Internet of Things Using a Multi-Objective Fuzzy-Based Hybrid Algorithm.

The Internet of Things (IoT) represents a cutting-edge technical domain, encompassing billions of intelligent objects capable of bridging the physical and virtual worlds across various locations. IoT services are responsible for delivering essential functionalities. In this dynamic and interconnected IoT landscape, providing high-quality services is paramount to enhancing user experiences and optimizing system efficiency. Service composition techniques come into play to address user requests in IoT applications, allowing various IoT services to collaborate seamlessly. Considering the resource limitations of IoT devices, they often leverage cloud infrastructures to overcome technological constraints, benefiting from unlimited resources and capabilities. Moreover, the emergence of fog computing has gained prominence, facilitating IoT application processing in edge networks closer to IoT sensors and effectively reducing delays inherent in cloud data centers. In this context, our study proposes a cloud-/fog-based service composition for IoT, introducing a novel fuzzy-based hybrid algorithm. This algorithm ingeniously combines Ant Colony Optimization (ACO) and Artificial Bee Colony (ABC) optimization algorithms, taking into account energy consumption and Quality of Service (QoS) factors during the service selection process. By leveraging this fuzzy-based hybrid algorithm, our approach aims to revolutionize service composition in IoT environments by empowering intelligent decision-making capabilities and ensuring optimal user satisfaction. Our experimental results demonstrate the effectiveness of the proposed strategy in successfully fulfilling service composition requests by identifying suitable services. When compared to recently introduced methods, our hybrid approach yields significant benefits. On average, it reduces energy consumption by 17.11%, enhances availability and reliability by 8.27% and 4.52%, respectively, and improves the average cost by 21.56%.

Effects of a Peptide Derived from the Primary Sequence of a Kallikrein Inhibitor Isolated from Bauhinia bauhinioides (pep-BbKI) in an Asthma-COPD Overlap (ACO) Model.

(1) There are several patients with asthma-COPD overlap (ACO). A peptide derived from the primary sequence of a kallikrein inhibitor isolated from Bauhinia bauhinioides (pep-BbKI) has potent anti-inflammatory and antioxidant effects. Purpose: To investigate the effects of pep-BbKI treatment in an ACO model and compare them with those of corticosteroids. (2) BALB/c mice were divided into groups: SAL (saline), OVA (ovalbumin), ELA (elastase), ACO (ovalbumin + elastase), ACO-pep-BbKI (treated with inhibitor), ACO-DX (dexamethasone treatment), ACO-DX-pep-BbKI (both treatments), and SAL-pep-BbKI (saline group treated with inhibitor). We evaluated: hyperresponsiveness to methacholine, bronchoalveolar lavage fluid (BALF), exhaled nitric oxide (eNO), IL-1ß, IL-4, IL-5, IL-6, IL-10, IL-13, IL-17, IFN-γ, TNF-α, MMP-9, MMP-12, TGF-ß, collagen fibers, iNOS, eNO, linear mean intercept (Lm), and NF-κB in airways (AW) and alveolar septa (AS). (3) ACO-pep-BbKI reversed ACO alterations and was similar to SAL in all mechanical parameters, Lm, neutrophils, IL-5, IL-10, IL-17, IFN-γ, TNF-α, MMP-12 (AW), collagen fibers, iNOS (AW), and eNO (p > 0.05). ACO-DX reversed ACO alterations and was similar to SAL in all mechanical parameters, Lm, total cells and differentials, IL-1ß(AS), IL-5 (AS), IL-6 (AS), IL-10 (AS), IL-13 (AS), IFN-γ, MMP-12 (AS), TGF-ß (AS), collagen fibers (AW), iNOS, and eNO (p > 0.05). SAL was similar to SAL-pep-BbKI for all comparisons (p > 0.05). (4) Pep-BbKI was similar to dexamethasone in reducing the majority of alterations of this ACO model.